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Raspin K, FitzGerald LM, Marthick JR, Field MA, Malley RC, Banks A, Donovan S, Thomson RJ, Foley GR, Stanford JL, Dickinson JL. A rare variant in EZH2 is associated with prostate cancer risk. Int J Cancer 2021; 149:1089-1099. [PMID: 33821477 DOI: 10.1002/ijc.33584] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 02/26/2021] [Accepted: 03/09/2021] [Indexed: 11/11/2022]
Abstract
Prostate cancer (PrCa) is highly heritable, and although rare variants contribute significantly to PrCa risk, few have been identified to date. Herein, whole-genome sequencing was performed in a large PrCa family featuring multiple affected relatives spanning several generations. A rare, predicted splice site EZH2 variant, rs78589034 (G > A), was identified as segregating with disease in all but two individuals in the family, one of whom was affected with lymphoma and bowel cancer and a female relative. This variant was significantly associated with disease risk in combined familial and sporadic PrCa datasets (n = 1551; odds ratio [OR] = 3.55, P = 1.20 × 10-5 ). Transcriptome analysis was performed on prostate tumour needle biopsies available for two rare variant carriers and two wild-type cases. Although no allele-dependent differences were detected in EZH2 transcripts, a distinct differential gene expression signature was observed when comparing prostate tissue from the rare variant carriers with the wild-type samples. The gene expression signature comprised known downstream targets of EZH2 and included the top-ranked genes, DUSP1, FOS, JUNB and EGR1, which were subsequently validated by qPCR. These data provide evidence that rs78589034 is associated with increased PrCa risk in Tasmanian men and further, that this variant may be associated with perturbed EZH2 function in prostate tissue. Disrupted EZH2 function is a driver of tumourigenesis in several cancers, including prostate, and is of significant interest as a therapeutic target.
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Affiliation(s)
- Kelsie Raspin
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Liesel M FitzGerald
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - James R Marthick
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Matt A Field
- Australian Institute of Tropical Health and Medicine and Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Cairns, Queensland, Australia.,John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Roslyn C Malley
- Hobart Pathology, Hobart, Tasmania, Australia.,Tasmanian School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Annette Banks
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | | | - Russell J Thomson
- Centre for Research in Mathematics and Data Science, Western Sydney University, Sydney, New South Wales, Australia
| | - Georgea R Foley
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Janet L Stanford
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Joanne L Dickinson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
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2
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Germline variants in IL4, MGMT and AKT1 are associated with prostate cancer-specific mortality: An analysis of 12,082 prostate cancer cases. Prostate Cancer Prostatic Dis 2018; 21:228-237. [PMID: 29298992 PMCID: PMC6026113 DOI: 10.1038/s41391-017-0029-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2017] [Revised: 11/09/2017] [Accepted: 11/20/2017] [Indexed: 02/08/2023]
Abstract
Background Prostate cancer (PCa) is a leading cause of mortality and genetic factors can influence tumour aggressiveness. Several germline variants have been associated with PCa-specific mortality (PCSM), but further replication evidence is needed. Methods Twenty-two previously identified PCSM-associated genetic variants were genotyped in seven PCa cohorts (12,082 patients; 1544 PCa deaths). For each cohort, Cox proportional hazards models were used to calculate hazard ratios and 95% confidence intervals for risk of PCSM associated with each variant. Data were then combined using a meta-analysis approach. Results Fifteen SNPs were associated with PCSM in at least one of the seven cohorts. In the meta-analysis, after adjustment for clinicopathological factors, variants in the MGMT (rs2308327; HR 0.90; p-value = 3.5 × 10−2) and IL4 (rs2070874; HR 1.22; p-value = 1.1 × 10−3) genes were confirmed to be associated with risk of PCSM. In analyses limited to men diagnosed with local or regional stage disease, a variant in AKT1, rs2494750, was also confirmed to be associated with PCSM risk (HR 0.81; p-value = 3.6 × 10−2). Conclusions This meta-analysis confirms the association of three genetic variants with risk of PCSM, providing further evidence that genetic background plays a role in PCa-specific survival. While these variants alone are not sufficient as prognostic biomarkers, these results may provide insights into the biological pathways modulating tumour aggressiveness.
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Lee M, Crawford NPS. Defining the Influence of Germline Variation on Metastasis Using Systems Genetics Approaches. Adv Cancer Res 2016; 132:73-109. [PMID: 27613130 DOI: 10.1016/bs.acr.2016.07.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Cancer is estimated to be responsible for 8 million deaths worldwide and over half a million deaths every year in the United States. The majority of cancer-related deaths in solid tumors is directly associated with the effects of metastasis. While the influence of germline factors on cancer risk and development has long been recognized, the contribution of hereditary variation to tumor progression and metastasis has only gained acceptance more recently. A variety of approaches have been used to define how hereditary variation influences tumor progression and metastasis. One approach that garnered much early attention was epidemiological studies of cohorts of cancer patients, which demonstrated that specific loci within the human genome are associated with a differential propensity for aggressive tumor development. However, a powerful, and somewhat underutilized approach has been the use of systems genetics approaches in transgenic mouse models of human cancer. Such approaches are typically multifaceted, and involve integration of multiple lines of evidence derived, for example, from genetic and transcriptomic screens of genetically diverse mouse models of cancer, coupled with bioinformatics analysis of human cancer datasets, and functional analysis of candidate genes. These methodologies have allowed for the identification of multiple hereditary metastasis susceptibility genes, with wide-ranging cellular functions including regulation of gene transcription, cell proliferation, and cell-cell adhesion. In this chapter, we review how each of these approaches have facilitated the identification of these hereditary metastasis modifiers, the molecular functions of these metastasis-associated genes, and the implications of these findings upon patient survival.
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Affiliation(s)
- M Lee
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, United States
| | - N P S Crawford
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, United States.
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Abstract
Although prostate cancer is the most common malignancy to affect men in the Western world, the molecular mechanisms underlying its development and progression remain poorly understood. Like all cancers, prostate cancer is a genetic disease that is characterized by multiple genomic alterations, including point mutations, microsatellite variations, and chromosomal alterations such as translocations, insertions, duplications, and deletions. In prostate cancer, but not other carcinomas, these chromosome alterations result in a high frequency of gene fusion events. The development and application of novel high-resolution technologies has significantly accelerated the detection of genomic alterations, revealing the complex nature and heterogeneity of the disease. The clinical heterogeneity of prostate cancer can be partly explained by this underlying genetic heterogeneity, which has been observed between patients from different geographical and ethnic populations, different individuals within these populations, different tumour foci within the same patient, and different cells within the same tumour focus. The highly heterogeneous nature of prostate cancer provides a real challenge for clinical disease management and a detailed understanding of the genetic alterations in all cells, including small subpopulations, would be highly advantageous.
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Abstract
Adhesion G protein-coupled receptors (aGPCRs) have a long evolutionary history dating back to very basal unicellular eukaryotes. Almost every vertebrate is equipped with a set of different aGPCRs. Genomic sequence data of several hundred extinct and extant species allows for reconstruction of aGPCR phylogeny in vertebrates and non-vertebrates in general but also provides a detailed view into the recent evolutionary history of human aGPCRs. Mining these sequence sources with bioinformatic tools can unveil many facets of formerly unappreciated aGPCR functions. In this review, we extracted such information from the literature and open public sources and provide insights into the history of aGPCR in humans. This includes comprehensive analyses of signatures of selection, variability of human aGPCR genes, and quantitative traits at human aGPCR loci. As indicated by a large number of genome-wide genotype-phenotype association studies, variations in aGPCR contribute to specific human phenotypes. Our survey demonstrates that aGPCRs are significantly involved in adaptation processes, phenotype variations, and diseases in humans.
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Affiliation(s)
- Peter Kovacs
- Integrated Research and Treatment Center (IFB) AdiposityDiseases, Medical Faculty, University of Leipzig, Liebigstr. 21, Leipzig, 04103, Germany.
| | - Torsten Schöneberg
- Institute of Biochemistry, Medical Faculty, University of Leipzig, Johannisallee 30, Leipzig, 04103, Germany.
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7
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Li Q, Gu C, Zhu Y, Wang M, Yang Y, Wang J, Jin L, Zhu ML, Shi TY, He J, Ye D, Wei Q. Two novel PRKCI polymorphisms and prostate cancer risk in an Eastern Chinese Han population. Mol Carcinog 2015; 54:632-41. [PMID: 24510606 DOI: 10.1002/mc.22130] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2013] [Revised: 12/05/2013] [Accepted: 12/19/2013] [Indexed: 02/05/2023]
Abstract
The atypical protein kinase C (aPKCι), encoded by the PRKCI gene, has been recently found to be a unique human oncoprotein, compared with some other diverse PKC isozymes. Genetic variations in PRKCI have also been reported to be associated with prostate cancer (PCa) risk in Caucasian populations, but no similar studies have been reported for Chinese populations. We genotyped two well-described PRKCI single nucleotide polymorphisms (SNPs) rs546950 and rs4955720 in 1015 PCa patients and 1044 cancer-free controls of Eastern Chinese men. SNPs in the vicinity of those two variants of PRKCI were evaluated using the in silico analysis. Logistic regression was then used to estimate their associations with and interactions in PCa risk. Although no significant main effects were found for the two tested SNPs in the single locus analysis, individuals carrying homozygote wide-type form of these two SNPs had slightly reduced PCa risk (adjusted OR = 0.63, 95% CI = 0.40-0.99, P = 0.045), compared with those carrying any of heterozygous or homozygous variant genotypes. Our results indicated that the two PRKCI SNPs were jointly associated with PCa risk in an Eastern Chinese population. Larger studies with multiethnic groups are warranted to confirm these findings and to explore the role of PRKCI SNPs in the etiology of PCa.
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Affiliation(s)
- Qiaoxin Li
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chengyuan Gu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yao Zhu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Mengyun Wang
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Jiucun Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Li Jin
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Mei-Ling Zhu
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ting-Yan Shi
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jing He
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Dingwei Ye
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Qingyi Wei
- Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina
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Eeles R, Goh C, Castro E, Bancroft E, Guy M, Al Olama AA, Easton D, Kote-Jarai Z. The genetic epidemiology of prostate cancer and its clinical implications. Nat Rev Urol 2014; 11:18-31. [PMID: 24296704 DOI: 10.1038/nrurol.2013.266] [Citation(s) in RCA: 178] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Worldwide, familial and epidemiological studies have generated considerable evidence of an inherited component to prostate cancer. Indeed, rare highly penetrant genetic mutations have been implicated. Genome-wide association studies (GWAS) have also identified 76 susceptibility loci associated with prostate cancer risk, which occur commonly but are of low penetrance. However, these mutations interact multiplicatively, which can result in substantially increased risk. Currently, approximately 30% of the familial risk is due to such variants. Evaluating the functional aspects of these variants would contribute to our understanding of prostate cancer aetiology and would enable population risk stratification for screening. Furthermore, understanding the genetic risks of prostate cancer might inform predictions of treatment responses and toxicities, with the goal of personalized therapy. However, risk modelling and clinical translational research are needed before we can translate risk profiles generated from these variants into use in the clinical setting for targeted screening and treatment.
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Affiliation(s)
- Rosalind Eeles
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Chee Goh
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Elena Castro
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Elizabeth Bancroft
- Clinical Academic Cancer Genetics Unit, The Royal Marsden NHS Foundation Trust, Sutton, Surrey SM2 5PT, UK
| | - Michelle Guy
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Ali Amin Al Olama
- Cancer Research UK Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, University of Cambridge, Cambridge CB1 8RN, UK
| | - Douglas Easton
- Departments of Public Health & Primary Care and Oncology, Strangeways Laboratory, University of Cambridge, Cambridge CB1 8RN, UK
| | - Zsofia Kote-Jarai
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
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9
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Rinella ES, Shao Y, Yackowski L, Pramanik S, Oratz R, Schnabel F, Guha S, LeDuc C, Campbell CL, Klugman SD, Terry MB, Senie RT, Andrulis IL, Daly M, John EM, Roses D, Chung WK, Ostrer H. Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation. Hum Genet 2013; 132:523-36. [PMID: 23354978 DOI: 10.1007/s00439-013-1269-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2012] [Accepted: 01/13/2013] [Indexed: 01/26/2023]
Abstract
The ability to establish genetic risk models is critical for early identification and optimal treatment of breast cancer. For such a model to gain clinical utility, more variants must be identified beyond those discovered in previous genome-wide association studies (GWAS). This is especially true for women at high risk because of family history, but without BRCA1/2 mutations. This study incorporates three datasets in a GWAS analysis of women with Ashkenazi Jewish (AJ) homogeneous ancestry. Two independent discovery cohorts comprised 239 and 238 AJ women with invasive breast cancer or preinvasive ductal carcinoma in situ and strong family histories of breast cancer, but lacking the three BRCA1/2 founder mutations, along with 294 and 230 AJ controls, respectively. An independent, third cohort of 203 AJ cases with familial breast cancer history and 263 healthy controls of AJ women was used for validation. A total of 19 SNPs were identified as associated with familial breast cancer risk in AJ women. Among these SNPs, 13 were identified from a panel of 109 discovery SNPs, including an FGFR2 haplotype. In addition, six previously identified breast cancer GWAS SNPs were confirmed in this population. Seven of the 19 markers were significant in a multivariate predictive model of familial breast cancer in AJ women, three novel SNPs [rs17663555(5q13.2), rs566164(6q21), and rs11075884(16q22.2)], the FGFR2 haplotype, and three previously published SNPs [rs13387042(2q35), rs2046210(ESR1), and rs3112612(TOX3)], yielding moderate predictive power with an area under the curve (AUC) of the ROC (receiver-operator characteristic curve) of 0.74. Population-specific genetic variants in addition to variants shared with populations of European ancestry may improve breast cancer risk prediction among AJ women from high-risk families without founder BRCA1/2 mutations.
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Affiliation(s)
- Erica S Rinella
- Department of Surgery, New York University Langone Medical Center, New York, NY, USA
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10
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Bailey-Wilson JE, Childs EJ, Cropp CD, Schaid DJ, Xu J, Camp NJ, Cannon-Albright LA, Farnham JM, George A, Powell I, Carpten JD, Giles GG, Hopper JL, Severi G, English DR, Foulkes WD, Mæhle L, Møller P, Eeles R, Easton D, Guy M, Edwards S, Badzioch MD, Whittemore AS, Oakley-Girvan I, Hsieh CL, Dimitrov L, Stanford JL, Karyadi DM, Deutsch K, McIntosh L, Ostrander EA, Wiley KE, Isaacs SD, Walsh PC, Thibodeau SN, McDonnell SK, Hebbring S, Lange EM, Cooney KA, Tammela TLJ, Schleutker J, Maier C, Bochum S, Hoegel J, Grönberg H, Wiklund F, Emanuelsson M, Cancel-Tassin G, Valeri A, Cussenot O, Isaacs WB. Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families. BMC MEDICAL GENETICS 2012; 13:46. [PMID: 22712434 PMCID: PMC3495053 DOI: 10.1186/1471-2350-13-46] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2011] [Accepted: 04/30/2012] [Indexed: 11/20/2022]
Abstract
BACKGROUND Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.
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Affiliation(s)
- Joan E Bailey-Wilson
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- University of Tampere ICPCG Group, Tampere, Finland
| | - Erica J Childs
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Cheryl D Cropp
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA
| | - Jianfeng Xu
- Data Coordinating Center for the ICPCG and Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Nicola J Camp
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Lisa A Cannon-Albright
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - James M Farnham
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Asha George
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Isaac Powell
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - John D Carpten
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- Translational Genomics Research Institute, Genetic Basis of Human Disease Research Division, Phoenix, AZ, USA
| | - Graham G Giles
- ACTANE consortium
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - John L Hopper
- ACTANE consortium
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Gianluca Severi
- ACTANE consortium
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Dallas R English
- ACTANE consortium
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - William D Foulkes
- ACTANE consortium
- Program in Cancer Genetics, McGill University, Montreal, QC, Canada
| | - Lovise Mæhle
- ACTANE consortium
- Department of Medical Genetics, Oslo University Hospital, The Norwegian Radium Hospital, Oslo,Norway
| | - Pål Møller
- ACTANE consortium
- Department of Medical Genetics, Oslo University Hospital, The Norwegian Radium Hospital, Oslo,Norway
| | - Rosalind Eeles
- ACTANE consortium
- Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Douglas Easton
- ACTANE consortium
- Cancer Research UK Genetic Epidemiology Unit, Cambridge, UK
| | - Michelle Guy
- ACTANE consortium
- Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Steve Edwards
- ACTANE consortium
- Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Michael D Badzioch
- ACTANE consortium
- Division of Medical Genetics, University of Washington Medical Center, Seattle, WA, USA
| | - Alice S Whittemore
- BC/CA/HI ICPCG Group, Stanford, CA, USA
- Department of Health Research and Policy, Stanford School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford School of Medicine, Stanford, CA, USA
| | - Ingrid Oakley-Girvan
- BC/CA/HI ICPCG Group, Stanford, CA, USA
- Department of Health Research and Policy, Stanford School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford School of Medicine, Stanford, CA, USA
- Cancer Prevention Institute of California
| | - Chih-Lin Hsieh
- BC/CA/HI ICPCG Group, Stanford, CA, USA
- Department of Urology and Department of Biochemistry and Molecular Biology, University of Southern California, Los Ageles, CA, USA
| | - Latchezar Dimitrov
- Data Coordinating Center for the ICPCG and Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Janet L Stanford
- FHCRC ICPCG Group, Seattle, WA, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
| | - Danielle M Karyadi
- FHCRC ICPCG Group, Seattle, WA, USA
- Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kerry Deutsch
- FHCRC ICPCG Group, Seattle, WA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Laura McIntosh
- FHCRC ICPCG Group, Seattle, WA, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
| | - Elaine A Ostrander
- FHCRC ICPCG Group, Seattle, WA, USA
- Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kathleen E Wiley
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Sarah D Isaacs
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Patrick C Walsh
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | | | | | | | - Ethan M Lange
- University of Michigan ICPCG Group, Ann Arbor, MI, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Kathleen A Cooney
- University of Michigan ICPCG Group, Ann Arbor, MI, USA
- University of Michigan, Ann Arbor, MI, USA
| | - Teuvo LJ Tammela
- University of Tampere ICPCG Group, Tampere, Finland
- Institute of Biomedical Technology, University of Tampere, Tampere, Finland
- Centre for Laboratory Medicine and Department of Urology, Tampere University Hospital, Tampere, Finland
| | - Johanna Schleutker
- University of Tampere ICPCG Group, Tampere, Finland
- Institute of Biomedical Technology, University of Tampere, Tampere, Finland
- Centre for Laboratory Medicine and Department of Urology, Tampere University Hospital, Tampere, Finland
| | - Christiane Maier
- University of Ulm ICPCG Group, Ulm, Germany
- Dept of Urology, University of Ulm, Ulm, Germany
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Sylvia Bochum
- University of Ulm ICPCG Group, Ulm, Germany
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Josef Hoegel
- University of Ulm ICPCG Group, Ulm, Germany
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | | | | | - Olivier Cussenot
- CeRePP ICPCG Group, 75020, Paris, France
- Hopital Tenon, Assistance Publique-Hopitaux de Paris, 75020, Paris, France
| | - William B Isaacs
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
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11
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Abstract
One hundred years ago, decades before the discovery of the structure of DNA, debate raged regarding how human traits were passed from one generation to the next. Phenotypes, including risk of disease, had long been recognized as having a familial component. Yet it was difficult to reconcile genetic segregation as described by Mendel with observations exhaustively documented by Karl Pearson and others regarding the normal distribution of human characteristics. In 1918, R. A. Fisher published his landmark article, "The Correlation Between Relatives on the Supposition of Mendelian Inheritance," bridging this divide and demonstrating that multiple alleles, all individually obeying Mendel's laws, account for the phenotypic variation observed in nature.Since that time, geneticists have sought to identify the link between genotype and phenotype. Trait-associated alleles vary in their frequency and degree of penetrance. Some minor alleles may approach a frequency of 50% in the human population, whereas others are present within only a few individuals. The spectrum for penetrance is similarly wide. These characteristics jointly determine the segregation pattern of a given trait, which, in turn, determine the method used to map the trait. Until recently, identification of rare, highly penetrant alleles was most practical. Revolutionary studies in genomics reported over the past decade have made interrogation of most of the spectrum of genetic variation feasible.The following article reviews recent discoveries in the genetic basis of inherited cancer risk and how these discoveries inform cancer biology and patient management. Although this article focuses on prostate cancer, the principles are generic for any cancer and, indeed, for any trait.
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Zhang X, Jing Y, Qin Y, Hunsucker S, Meng H, Sui J, Jiang Y, Gao L, An G, Yang N, Orlowski RZ, Yang L. The zinc finger transcription factor ZKSCAN3 promotes prostate cancer cell migration. Int J Biochem Cell Biol 2012; 44:1166-73. [PMID: 22531714 DOI: 10.1016/j.biocel.2012.04.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Revised: 04/03/2012] [Accepted: 04/09/2012] [Indexed: 12/01/2022]
Abstract
In our previous studies, ZKSCAN3 was demonstrated to be over-expressed in invasive colonic tumor cells and their liver metastases, but minimally expressed in adjacent non-transformed tissues. Further preliminary data showed that ZKSCAN3 was expressed in a majority of prostate cancer patient samples, but not in normal prostate tissues. Moreover, the ZKSCAN3 protein is highly expressed in the PC3 prostate cancer cell line, which has high metastatic potential, but little expression was observed in non-metastatic prostate cancer cell lines. Thus, we hypothesized that ZKSCAN3 could participate in tumor metastasis by regulating tumor cell migration. To test this hypothesis, ZKSCAN3 mRNA was knocked down by ZKSCAN3 specific shRNA in PC3 cells and a significant decrease in cell motility was observed. In contrast, when ZKSCAN3 cDNA was overexpressed in PC3 cells, cell detachment was observed and suspension culture induced apoptosis was greatly decreased, suggesting that ZKSCAN3 is able to enhance PC3 cell survival under anoikis stress. Additional wound healing and invasion assays showed that cell migration was enhanced by ZKSCAN3 expression. Interestingly, the ZKSCAN3 gene was amplified in 26% (5/19) of metastatic prostate cancers and 20% (1/5) of lymph node metastases, but there was no amplification found in primary prostate cancers, further supporting the role of ZKSCAN3 in tumor cell migration. In vivo studies using orthotopic tumor models indicated that overexpression of ZKSCAN3 significantly enhanced tumorigenicity. Taken together, we provide evidence that ZKSCAN3, a zinc finger transcription factor, plays a critical role in promoting prostate cancer cell migration.
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Affiliation(s)
- Xingding Zhang
- Cyrus Tang Hematology Center, Soochow University, Suzhou, Jiangsu, PR China
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13
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Cheng Y, Liu W, Kim ST, Sun J, Lu L, Sun J, Zheng SL, Isaacs WB, Xu J. Evaluation of PPP2R2A as a prostate cancer susceptibility gene: a comprehensive germline and somatic study. Cancer Genet 2011; 204:375-81. [PMID: 21872824 DOI: 10.1016/j.cancergen.2011.05.002] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2011] [Revised: 04/28/2011] [Accepted: 05/05/2011] [Indexed: 12/22/2022]
Abstract
PPP2R2A, mapped to 8p21.2, codes for the α isoform of the regulatory B55 subfamily of protein phosphatase 2 (PP2A). PP2A is one of the four major serine/threonine phosphatases and is implicated in the negative control of cell growth and division. Because of its known functions and location within a chromosomal region where evidence for linkage and somatic loss of heterozygosity was found, we hypothesized that either somatic copy number changes or germline sequence variants in PPP2R2A may increase prostate cancer (PCa) risk. We examined PPP2R2A deletion status in 141 PCa samples using Affymetrix SNP arrays. It was found that PPP2R2A was commonly (67.1%) deleted in tumor samples, including a homozygous deletion in three tumors (2.1%). We performed a mutation screen for PPP2R2A in 96 probands of hereditary prostate cancer families. No high risk mutations were identified. In addition, we re-analyzed 10 SNPs of PPP2R2A in sporadic PCa cases and controls. No significant differences in the allele and genotype frequencies were observed among either PCa cases and controls or PCa aggressive and non-aggressive cases. Taken together, these results suggest that a somatic deletion rather than germline sequence variants of PPP2R2A may play a more important role in PCa susceptibility.
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Affiliation(s)
- Yu Cheng
- Center for Cancer Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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14
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Abstract
For decades, physicians and researchers have recognized that family history is a significant risk factor for prostate cancer. The identification of the genes responsible for inherited risk, however, proved difficult. With the sequencing of the human genome and the completion of the initial phases of the International HapMap Project, the tools are available to scan the entire genome and find genetic markers for disease. Since 2006, more than 30 inherited variants strongly associated with prostate cancer have been reported. As the inherited component of the disease is revealed, efforts are ongoing to translate genetic findings into the clinic.
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Affiliation(s)
- Mark M Pomerantz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
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15
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Johanneson B, McDonnell SK, Karyadi DM, Quignon P, McIntosh L, Riska SM, FitzGerald LM, Johnson G, Deutsch K, Williams G, Tillmans LS, Stanford JL, Schaid DJ, Thibodeau SN, Ostrander EA. Family-based association analysis of 42 hereditary prostate cancer families identifies the Apolipoprotein L3 region on chromosome 22q12 as a risk locus. Hum Mol Genet 2010; 19:3852-62. [PMID: 20631155 DOI: 10.1093/hmg/ddq283] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Multiple genome-wide scans for hereditary prostate cancer (HPC) have identified susceptibility loci on nearly every chromosome. However, few results have been replicated with statistical significance. One exception is chromosome 22q, for which five independent linkage studies yielded strong evidence for a susceptibility locus in HPC families. Previously, we refined this region to a 2.53 Mb interval, using recombination mapping in 42 linked pedigrees. We now refine this locus to a 15 kb interval, spanning Apolipoprotein L3 (APOL3), using family-based association analyses of 150 total prostate cancer (PC) cases from two independent family collections with 506 unrelated population controls. Analysis of the two independent sets of PC cases highlighted single nucleotide polymorphisms (SNPs) within the APOL3 locus showing the strongest associations with HPC risk, with the most robust results observed when all 150 cases were combined. Analysis of 15 tagSNPs across the 5' end of the locus identified six SNPs with P-values < or =2 × 10(-4). The two independent sets of HPC cases highlight the same 15 kb interval at the 5' end of the APOL3 gene and provide strong evidence that SNPs within this 15 kb interval, or in strong linkage disequilibrium with it, contribute to HPC risk. Further analyses of this locus in an independent population-based, case-control study revealed an association between an SNP within the APOL3 locus and PC risk, which was not confirmed in the Cancer Genetic Markers of Susceptibility data set. This study further characterizes the 22q locus in HPC risk and suggests that the role of this region in sporadic PC warrants additional studies.
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Affiliation(s)
- Bo Johanneson
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50, Room 5351, Bethesda, MD 20892, USA
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16
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Fitzgerald LM, McDonnell SK, Carlson EE, Langeberg W, McIntosh LM, Deutsch K, Ostrander EA, Schaid DJ, Stanford JL. Genome-wide linkage analyses of hereditary prostate cancer families with colon cancer provide further evidence for a susceptibility locus on 15q11-q14. Eur J Hum Genet 2010; 18:1141-7. [PMID: 20407467 DOI: 10.1038/ejhg.2010.49] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The search for susceptibility loci in hereditary prostate cancer (HPC) is challenging because of locus and disease heterogeneity. One approach to reduce disease heterogeneity is to stratify families on the basis of the occurrence of multiple cancer types. This method may increase the power for detecting susceptibility loci, including those with pleiotropic effects. We have completed a genome-wide SNP linkage analysis of 96 HPC families, each of which has one or more first-degree relatives with colon cancer (CCa), and further analyzed the subset of families with two or more CCa cases (n = 27). When only a prostate cancer (PCa) phenotype was considered to be affected, we observed suggestive evidence for linkage (LOD ≥1.86) at 15q14, 18q21 and 19q13 in all families, and at 1p32 and 15q11-q14 in families with two or more CCa cases. When both the PCa and CCa phenotypes were considered affected, suggestive evidence for linkage was observed at 11q25, 15q14 and 18q21 in all families, and at 1q31, 11q14 and 15q11-14 in families with two or more CCa cases. The strongest linkage signal was identified at 15q14 when both PCa and CCa phenotypes were considered to be affected in families with two or more CCa cases (recessive HLOD = 3.88). These results provide further support for the presence of HPC susceptibility loci on chromosomes 11q14, 15q11-q14 and 19q13 and highlight loci at 1q31, 11q, 15q11-14 and 18q21 as having possible pleiotropic effects. This study shows the benefit of using a comprehensive family cancer history to create more genetically homogenous subsets of HPC families for linkage analyses.
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Affiliation(s)
- Liesel M Fitzgerald
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA
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17
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Stanford JL, FitzGerald LM, McDonnell SK, Carlson EE, McIntosh LM, Deutsch K, Hood L, Ostrander EA, Schaid DJ. Dense genome-wide SNP linkage scan in 301 hereditary prostate cancer families identifies multiple regions with suggestive evidence for linkage. Hum Mol Genet 2009; 18:1839-48. [PMID: 19251732 DOI: 10.1093/hmg/ddp100] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The search for susceptibility loci in hereditary prostate cancer (HPC) has proven challenging due to genetic and disease heterogeneity. Multiple risk loci have been identified to date, however few loci have been replicated across independent linkage studies. In addition, most previous analyses have been hampered by the relatively poor information content provided by microsatellite scans. To overcome these issues, we have performed linkage analyses on members of 301 HPC families genotyped using the Illumina SNP linkage panel IVb. The information content for this panel, averaged over all pedigrees and all chromosomes, was 86% (range 83-87% over chromosomes). Analyses were also stratified on families according to disease aggressiveness, age at diagnosis and number of affected individuals to achieve more genetically homogeneous subsets. Suggestive evidence for linkage was identified at 7q21 (HLOD = 1.87), 8q22 (KCLOD = 1.88) and 15q13-q14 (HLOD = 1.99) in 289 Caucasian families, and nominal evidence for linkage was identified at 2q24 (LOD = 1.73) in 12 African American families. Analysis of more aggressive prostate cancer phenotypes provided evidence for linkage to 11q25 (KCLOD = 2.02), 15q26 (HLOD = 1.99) and 17p12 (HLOD = 2.13). Subset analyses according to age at diagnosis and number of affected individuals also identified several regions with suggestive evidence for linkage, including a KCLOD of 2.82 at 15q13-q14 in 128 Caucasian families with younger ages at diagnosis. The results presented here provide further evidence for a prostate cancer susceptibility locus on chromosome 15q and demonstrate the power of utilizing high information content SNP scans in combination with homogenous collections of large prostate cancer pedigrees.
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Affiliation(s)
- Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
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18
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Ostrander EA, Udler MS. The role of the BRCA2 gene in susceptibility to prostate cancer revisited. Cancer Epidemiol Biomarkers Prev 2008; 17:1843-8. [PMID: 18708369 DOI: 10.1158/1055-9965.epi-08-0556] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Prostate cancer is a genetically complex disease with multiple predisposing factors affecting presentation, progression, and outcome. Epidemiologic studies have long shown an aggregation of breast and prostate cancer in some families. More recently, studies have reported an apparent excess of prostate cancer cases among BRCA2 mutation-carrying families. Additionally, population-based screens of early-onset prostate cancer patients have suggested that the prevalence of deleterious BRCA2 mutations in this group is 1% to 2%, imparting a significantly increased risk of the disease compared with noncarrier cases. However, studies of high-risk prostate cancer families suggest that BRCA2 plays at most a minimal role in these individuals, highlighting the potential genetic heterogeneity of the disease. In this commentary, we review the current literature and hypotheses surrounding the relationship between BRCA2 mutations and susceptibility to prostate cancer and speculate on the potential for involvement of additional genes.
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Affiliation(s)
- Elaine A Ostrander
- Cancer Genetic Branch, National Human Genome Research Institute, NIH, Room 52451, Building 50, Bethesda, MD 20892, USA.
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19
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Tischkowitz MD, Yilmaz A, Chen LQ, Karyadi DM, Novak D, Kirchhoff T, Hamel N, Tavtigian SV, Kolb S, Bismar TA, Aloyz R, Nelson PS, Hood L, Narod SA, White KA, Ostrander EA, Isaacs WB, Offit K, Cooney KA, Stanford JL, Foulkes WD. Identification and characterization of novel SNPs in CHEK2 in Ashkenazi Jewish men with prostate cancer. Cancer Lett 2008; 270:173-80. [PMID: 18571837 DOI: 10.1016/j.canlet.2008.05.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2008] [Revised: 01/17/2008] [Accepted: 05/06/2008] [Indexed: 11/26/2022]
Abstract
Checkpoint kinase 2 (CHEK2) is a protein involved in arresting cell cycle in response to DNA damage. To investigate whether it plays an important role in the development of prostate cancer (PRCA) in the Ashkenazi Jewish (AJ) population, we sequenced CHEK2 in 75 AJ individuals with prostate, breast, or no cancer (n=25 each). We identified seven coding SNPs (five are novel) that changed the amino-acid sequence, resulting in R3W, E394F, Y424H, S428F, D438Y, P509S, and P509L. We determined the frequency of each variant in 76 AJ families collected by members of the International Consortium for Prostate Cancer Genetics (ICPCG) where >or=2 men were affected by PRCA. Only one variant, Y424H in exon 11, was identified in more than two families. Exon 11 was then screened in nine additional AJ ICPCG families (a total of 85 families). The Y424H variant occurred in nine affected cases from four different families; however, it did not completely segregate with the disease. We performed bioinformatics analysis, which showed that Y424H is a non-conservative missense substitution that falls at a position that is invariant in vertebrate CHEK2 orthologs. Both SIFT and Align-GVGD predict that Y424H is a loss of function mutation. However, the frequency of Y424H was not significantly different between unselected AJ cases from Montreal/Memorial Sloan Kettering Cancer Centre (MSKCC) and AJ controls from Israel/MSKCC (OR 1.18, 95%CI: 0.34-4.61, p=.99). Moreover, functional assays using Saccharomyces cerevisiae revealed that the Y424H substitution did not alter function of CHEK2 protein. Although we cannot rule out a subtle influence of the CHEK2 variants on PRCA risk, these results suggest that germline CHEK2 mutations have a minor role in, if any, PRCA susceptibility in AJ men.
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Affiliation(s)
- Marc D Tischkowitz
- Department of Oncology and Medical Genetics, Cancer Prevention Centre, E740, Sir MB Davis-Jewish General Hospital, McGill University, Montreal, QC, Canada
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20
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Schaid DJ, McDonnell SK, Carlson EE, Thibodeau SN, Stanford JL, Ostrander EA. Searching for epistasis and linkage heterogeneity by correlations of pedigree-specific linkage scores. Genet Epidemiol 2008; 32:464-75. [PMID: 18330905 DOI: 10.1002/gepi.20319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Recognizing that multiple genes are likely responsible for common complex traits, statistical methods are needed to rapidly screen for either interacting genes or locus heterogeneity in genetic linkage data. To achieve this, some investigators have proposed examining the correlation of pedigree linkage scores between pairs of chromosomal regions, because large positive correlations suggest interacting loci and large negative correlations suggest locus heterogeneity (Cox et al. [1999]; Maclean et al. [1993]). However, the statistical significance of these extreme correlations has been difficult to determine due to the autocorrelation of linkage scores along chromosomes. In this study, we provide novel solutions to this problem by using results from random field theory, combined with simulations to determine the null correlation for syntenic loci. Simulations illustrate that our new methods control the Type-I error rates, so that one can avoid the extremely conservative Bonferroni correction, as well as the extremely time-consuming permutational method to compute P-values for non-syntenic loci. Application of these methods to prostate cancer linkage studies illustrates interpretation of results and provides insights into the impact of marker information content on the resulting statistical correlations, and ultimately the asymptotic P-values.
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Affiliation(s)
- Daniel J Schaid
- Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
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21
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Hood L. A personal journey of discovery: developing technology and changing biology. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2008; 1:1-43. [PMID: 20636073 DOI: 10.1146/annurev.anchem.1.031207.113113] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
This autobiographical article describes my experiences in developing chemically based, biological technologies for deciphering biological information: DNA, RNA, proteins, interactions, and networks. The instruments developed include protein and DNA sequencers and synthesizers, as well as ink-jet technology for synthesizing DNA chips. Diverse new strategies for doing biology also arose from novel applications of these instruments. The functioning of these instruments can be integrated to generate powerful new approaches to cloning and characterizing genes from a small amount of protein sequence or to using gene sequences to synthesize peptide fragments so as to characterize various properties of the proteins. I also discuss the five paradigm changes in which I have participated: the development and integration of biological instrumentation; the human genome project; cross-disciplinary biology; systems biology; and predictive, personalized, preventive, and participatory (P4) medicine. Finally, I discuss the origins, the philosophy, some accomplishments, and the future trajectories of the Institute for Systems Biology.
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Affiliation(s)
- Lee Hood
- Institute for Systems Biology, Seattle, Washington 98103, USA.
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22
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Ostrander EA, Johannesson B. Prostate cancer susceptibility loci: finding the genes. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2008; 617:179-90. [PMID: 18497042 DOI: 10.1007/978-0-387-69080-3_17] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
Abstract
Studies to date suggest that PC is a genetically very heterogeneous disease. High-risk families, in which multiple men are affected likely, reflect the contributions of a number of genes, some that are rare and highly penetrant, while others are more common and weakly penetrant. In this review, we have discussed only the first type of loci, and found that the identification of such genomic regions is a formidable problem. Replication between seemingly similar data sets is weak, likely reflecting the older age of onset associated with the disease, the inability to collect affected individuals from more than two generations in a family, and the variation seen in disease presentation, in addition to the underlying locus heterogeneity. Indeed, the definition of PC is ever changing, as diagnostic criteria and tools for pinpointing early lesions improve. Are we making progress? Clearly the answer is yes. The ability to divide large data sets into homogenous subset of families likely to share common genetic under-pinnings has improved power to identify loci and reproducibility between loci is now more common. Indeed, several groups report linkage to loci on chromosomes 1, 17, 19, and 22. Key to our continued success is our ever increasing ability to understand the disease. Identifying the subset of men who are likely to get clinically significant disease is the goal of genetic studies like these, and identifying the underlying loci is the key for developing diagnostics. The willingness of the community to work together has been an important factor in the successes the community has enjoyed to date, and will likely be as important as we move forward to untangle the genetics of this complex and common disorder.
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Affiliation(s)
- Elanie A Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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23
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Fine mapping of familial prostate cancer families narrows the interval for a susceptibility locus on chromosome 22q12.3 to 1.36 Mb. Hum Genet 2007; 123:65-75. [PMID: 18066601 DOI: 10.1007/s00439-007-0451-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2007] [Accepted: 12/02/2007] [Indexed: 10/22/2022]
Abstract
Genetic studies suggest that hereditary prostate cancer is a genetically heterogeneous disease with multiple contributing loci. Studies of high-risk prostate cancer families selected for aggressive disease, analysis of large multigenerational families, and a meta-analysis from the International Consortium for Prostate Cancer Genetics (ICPCG), all highlight chromosome 22q12.3 as a susceptibility locus with strong statistical significance. Recently, two publications have narrowed the 22q12.3 locus to a 2.18 Mb interval using 54 high-risk families from the ICPCG collaboration, as defined by three recombination events on either side of the locus. In this paper, we present the results from fine mapping studies at 22q12.3 using both haplotype and recombination data from 42 high-risk families contributed from the Mayo Clinic and the Prostate Cancer Genetic Research Study (PROGRESS) mapping studies. No clear consensus interval is present when all families are used. However, in the subset of 14 families with >/=5 affected men per family, a 2.53-Mb shared consensus segment that overlaps with the previously published interval is identified. Combining these results with data from the earlier ICPCG study reduces the three-recombination interval at 22q12.3 to approximately 1.36 Mb.
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Antón Aparicio LM, García Campelo R, Cassinello Espinosa J, Valladares Ayerbes M, Reboredo López M, Díaz Prado S, Aparicio Gallego G. Prostate cancer and Hedgehog signalling pathway. Clin Transl Oncol 2007; 9:420-8. [PMID: 17652055 DOI: 10.1007/s12094-007-0080-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
The Hedgehog (Hh) family of intercellular signalling proteins have come to be recognised as key mediators in many fundamental processes in embryonic development. Their activities are central to the growth, patterning and morphogenesis of many different regions within the bodies of vertebrates. In some contexts, Hh signals act as morphogens in the dose-dependent induction of distinct cell fates within a target field, in others as mitogens in the regulation of cell proliferation or as inducing factors controlling the form of a developing organ. These diverse functions of Hh proteins raise many intriguing questions about their mode of action. Various studies have now demonstrated the function of Hh signalling in the control of cell proliferation, especially for stem cells and stem-like progenitors. Abnormal activation of the Hh pathway has been demonstrated in a variety of human tumours. Hh pathway activity in these tumours is required for cancer cell proliferation and tumour growth. Recent studies have uncovered the role for Hh signalling in advanced prostate cancer and demonstrated that autocrine signalling by tumour cells is required for proliferation, viability and invasive behaviour. Thus, Hh signalling represents a novel pathway in prostate cancer that offers opportunities for prognostic biomarker development, drug targeting and therapeutic response monitoring.
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Affiliation(s)
- L M Antón Aparicio
- Medical Oncology Service, C.H.U. Juan Canalejo, Department of Medicine, University of La Coruña, A Coruña, Spain.
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25
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Ostrander EA, Kwon EM, Stanford JL. Genetic susceptibility to aggressive prostate cancer. Cancer Epidemiol Biomarkers Prev 2007; 15:1761-4. [PMID: 17035380 DOI: 10.1158/1055-9965.epi-06-0730] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Elaine A Ostrander
- Cancer Genetics Branch, National Human Genome Research Institute, NIH, 50 South Drive, Bethesda, MD 20892, USA.
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26
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Suuriniemi M, Agalliu I, Schaid DJ, Johanneson B, McDonnell SK, Iwasaki L, Stanford JL, Ostrander EA. Confirmation of a positive association between prostate cancer risk and a locus at chromosome 8q24. Cancer Epidemiol Biomarkers Prev 2007; 16:809-14. [PMID: 17416775 DOI: 10.1158/1055-9965.epi-06-1049] [Citation(s) in RCA: 80] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Family-based linkage studies, association studies, and studies of tumors have highlighted human chromosome 8q as a genomic region of interest for prostate cancer susceptibility loci. Recently, a locus at 8q24, characterized by both a single nucleotide polymorphism (SNP) and a microsatellite marker, was shown to be associated with prostate cancer risk in Icelandic, Swedish, and U.S. samples. Although the data were provocative, the U.S. samples were not population based, which precludes assessment of the potential contribution of this locus to prostate cancer incidence in the United States. METHODS We analyzed both markers in a population-based, case-control study of middle-aged men from King County, Washington. RESULTS Overall, there was a significant positive association between the A allele of the SNP rs1447295 and prostate cancer risk [odds ratio, 1.4; 95% confidence interval (95% CI), 1.1-2.0] but no significant association with the microsatellite DG8S737. However, significant associations were observed for both markers in men with high Gleason scores. Adjusting for age, first-degree family history of prostate cancer, and prostate cancer screening history, the adjusted odds ratios were 1.4 (95% CI, 1.1-1.8) for the A allele of the SNP and 1.9 (95% CI, 1.2-2.8) for the -10 allele of the microsatellite. CONCLUSIONS These data suggest that the locus on chromosome 8q24 harbors a genetic variant associated with prostate cancer and that the microsatellite marker is a stronger risk factor for aggressive prostate cancers defined by poorly differentiated tumor morphology.
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Affiliation(s)
- Miia Suuriniemi
- Cancer Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
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27
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Camp NJ, Cannon-Albright LA, Farnham JM, Baffoe-Bonnie AB, George A, Powell I, Bailey-Wilson JE, Carpten JD, Giles GG, Hopper JL, Severi G, English DR, Foulkes WD, Maehle L, Moller P, Eeles R, Easton D, Badzioch MD, Whittemore AS, Oakley-Girvan I, Hsieh CL, Dimitrov L, Xu J, Stanford JL, Johanneson B, Deutsch K, McIntosh L, Ostrander EA, Wiley KE, Isaacs SD, Walsh PC, Thibodeau SN, McDonnell SK, Hebbring S, Schaid DJ, Lange EM, Cooney KA, Tammela TLJ, Schleutker J, Paiss T, Maier C, Grönberg H, Wiklund F, Emanuelsson M, Isaacs WB. Compelling evidence for a prostate cancer gene at 22q12.3 by the International Consortium for Prostate Cancer Genetics. Hum Mol Genet 2007; 16:1271-8. [PMID: 17478474 PMCID: PMC2653215 DOI: 10.1093/hmg/ddm075] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Previously, an analysis of 14 extended, high-risk Utah pedigrees localized in the chromosome 22q linkage region to 3.2 Mb at 22q12.3-13.1 (flanked on each side by three recombinants) contained 31 annotated genes. In this large, multi-centered, collaborative study, we performed statistical recombinant mapping in 54 pedigrees selected to be informative for recombinant mapping from nine member groups of the International Consortium for Prostate Cancer Genetics (ICPCG). These 54 pedigrees included the 14 extended pedigrees from Utah and 40 pedigrees from eight other ICPCG member groups. The additional 40 pedigrees were selected from a total pool of 1213 such that each pedigree was required to contain both at least four prostate cancer (PRCA) cases and exhibit evidence for linkage to the chromosome 22q region. The recombinant events in these 40 independent pedigrees confirmed the previously proposed region. Further, when all 54 pedigrees were considered, the three-recombinant consensus region was narrowed down by more than a megabase to 2.2 Mb at chromosome 22q12.3 flanked by D22S281 and D22S683. This narrower region eliminated 20 annotated genes from that previously proposed, leaving only 11 genes. This region at 22q12.3 is the most consistently identified and smallest linkage region for PRCA. This collaborative study by the ICPCG illustrates the value of consortium efforts and the continued utility of linkage analysis using informative pedigrees to localize genes for complex diseases.
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Affiliation(s)
- Nicola J Camp
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, 391 Chipeta Way, Suite D, Salt Lake City, UT 84108, USA.
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Johanneson B, Deutsch K, McIntosh L, Friedrichsen-Karyadi DM, Janer M, Kwon EM, Iwasaki L, Hood L, Ostrander EA, Stanford JL. Suggestive genetic linkage to chromosome 11p11.2-q12.2 in hereditary prostate cancer families with primary kidney cancer. Prostate 2007; 67:732-42. [PMID: 17372923 DOI: 10.1002/pros.20528] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND The Seattle-based PROGRESS study was started in 1995 to ascertain hereditary prostate cancer (HPC) families for studies of genetic susceptibility. Subsequent studies by several research groups, including our own, suggest that HPC is a genetically heterogeneous disease. To be successful in mapping loci for such a complex disease, one must consider ways of grouping families into subsets that likely share the same genetic origin. Towards that end, we analyzed a genome-wide scan of HPC families with primary kidney cancer. METHODS An 8.1 cM genome-wide scan including 441 microsatellite markers was analyzed by both parametric and non-parametric linkage approaches in fifteen HPC families with the co-occurrence of kidney cancer. RESULTS There was no evidence for significant linkage in the initial findings. However, two regions of suggestive linkage were observed at 11q12 and 4q21, with HLOD scores of 2.59 and 2.10, respectively. The primary result on chromosome 11 was strengthened after excluding two families with members who had rare transitional cell carcinoma (TCC). Specifically, we observed a non-parametric Kong and Cox P-value of 0.004 for marker D11S1290 at 11p11.2. The 8 cM region between 11p11.2 and 11q12.2 was refined by the addition of 16 new markers. The subset of HPC families with a median age of diagnosis >65 years demonstrated the strongest evidence for linkage, with an HLOD = 2.50. The P-values associated with non-parametric analysis ranged from 0.004 to 0.05 across five contiguous markers. CONCLUSIONS Analysis of HPC families with members diagnosed with primary renal cell carcinoma demonstrates suggestive linkage to chromosome 11p11.2-q12.2.
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Affiliation(s)
- Bo Johanneson
- Cancer Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, USA
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Schaid DJ, Stanford JL, McDonnell SK, Suuriniemi M, McIntosh L, Karyadi DM, Carlson EE, Deutsch K, Janer M, Hood L, Ostrander EA. Genome-wide linkage scan of prostate cancer Gleason score and confirmation of chromosome 19q. Hum Genet 2007; 121:729-35. [PMID: 17486369 DOI: 10.1007/s00439-007-0368-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2007] [Accepted: 04/12/2007] [Indexed: 11/26/2022]
Abstract
Despite evidence that prostate cancer has a genetic etiology, it has been extremely difficult to confirm genetic linkage results across studies, emphasizing the large extent of genetic heterogeneity associated with this disease. Because prostate cancer is common--approximately one in six men will be diagnosed with prostate cancer in their life--genetic linkage studies are likely plagued by phenocopies (i.e., men with prostate cancer due to environmental or lifestyle factors), weakly penetrant alleles, or a combination of both, making it difficult to replicate linkage findings. One way to account for heterogeneous causes is to use clinical information that is related to the aggressiveness of disease as an endpoint for linkage analyses. Gleason grade is a measure of prostate tumor differentiation, with higher grades associated with more aggressive disease. This semi-quantitative score has been used as a quantitative trait for linkage analysis in several prior studies. Our aim was to determine if prior linkage reports of Gleason grade to specific loci could be replicated, and to ascertain if new regions of linkage could be found. Gleason scores were available for 391 affected sib pairs from 183 hereditary prostate cancer pedigrees as part of the PROGRESS study. Analyzing Gleason score as a quantitative trait, and using microsatellite markers, suggestive evidence for linkage (P-value <or= 0.001) was found on chromosomes 19q and 5q, with P-values <or= 0.01 observed on chromosomes 3q, 7q, and 16q. Our results confirm reports of Gleason score linkage to chromosome 19q and suggest new loci for further investigation.
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Agalliu I, Kwon EM, Zadory D, McIntosh L, Thompson J, Stanford JL, Ostrander EA. Germline mutations in the BRCA2 gene and susceptibility to hereditary prostate cancer. Clin Cancer Res 2007; 13:839-43. [PMID: 17289875 DOI: 10.1158/1078-0432.ccr-06-2164] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE Several epidemiologic studies have reported that carriers of germline mutations in the BRCA2 gene have an increased risk of prostate cancer, with the highest risk observed in men diagnosed at earlier ages. However, studies of the contribution of BRCA2 mutations to the etiology of hereditary prostate cancer (HPC) have been inconsistent. EXPERIMENTAL DESIGN To further address this issue, 266 subjects from 194 HPC families participating in the Seattle-based Prostate Cancer Genetic Research Study were screened for BRCA2 mutations by sequencing the coding regions, intron-exon boundaries, and suspected regulatory elements of this gene. Of selected HPC families, 32 had multiple breast or ovarian cancer cases, 16 were Jewish, 8 had a pancreatic cancer case, and 138 had at least one affected man diagnosed with prostate cancer at an early age (<60 years). RESULTS No disease-associated protein truncating BRCA2 mutations were found in 266 subjects from HPC families. There were 61 DNA sequence variants, of which 31 (50.8%) changed the predicted amino acids. No associations were found between these missense changes and family characteristics. Among affected men with prostate cancer, there were no statistically significant differences between the genotype frequencies of DNA variants with a minor allele frequency of 1% or higher and between the strata defined by median age at diagnosis or by clinical features. CONCLUSION No evidence was found in this study for an association between BRCA2 mutations and susceptibility to HPC in men selected from high-risk families.
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Affiliation(s)
- Ilir Agalliu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, USA
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Christensen GB, Camp NJ, Farnham JM, Cannon-Albright LA. Genome-wide linkage analysis for aggressive prostate cancer in Utah high-risk pedigrees. Prostate 2007; 67:605-13. [PMID: 17299800 DOI: 10.1002/pros.20554] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND It has been proposed that studying alternative phenotypes, such as tumor aggressiveness, may be a solution for overcoming the apparent heterogeneity that has hindered the identification of prostate cancer (PC) genes. We present the results of a genome-scan for predisposition to aggressive PC using the Utah high-risk pedigree resource. METHODS We identified 259 subjects with aggressive PC in 57 extended and nuclear families. Parametric and non-parametric multipoint linkage statistics were calculated for a genome-wide set of 401 microsatellite markers using the MCLINK software package. Stratification analyses by the number of affected subjects per pedigree (<5, >or=5) and the average age at diagnosis of affected subjects (<70 years, >or=70 years) were also performed. RESULTS No significant results were observed at the genome-wide level, but suggestive evidence for linkage was observed on chromosomes 9q (HLOD = 2.04) and 14q (HLOD = 2.08); several pedigrees showed individual evidence for linkage at each locus (LOD > 0.58). The subset of pedigrees with earlier age at onset demonstrated nominal linkage evidence on chromosomes 3q (HLOD = 1.79), 8q (HLOD = 1.67), and 20q (HLOD=1.82). The late-onset subset showed suggestive linkage on chromosome 6p (HLOD = 2.37) and the subset of pedigrees with fewer than five affected subjects showed suggestive linkage on chromosome 10p (HLOD = 1.99). CONCLUSIONS Linkage evidence observed on chromosomes 6p, 8q, and 20q support previously reported PC aggressiveness loci. While these results are encouraging, further research is necessary to identify the gene or genes responsible for PC aggressiveness and surmount the overarching problem of PC heterogeneity.
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Affiliation(s)
- G B Christensen
- Department of Biomedical Informatics, University of Utah School of Medicine, Utah, USA.
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Schaid DJ, McDonnell SK, Carlson EE, Thibodeau SN, Ostrander EA, Stanford JL. Affected relative pairs and simultaneous search for two-locus linkage in the presence of epistasis. Genet Epidemiol 2007; 31:431-49. [PMID: 17410530 DOI: 10.1002/gepi.20223] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
It is commonly believed that multiple interacting genes increase the susceptibility of genetically complex diseases, yet few linkage analyses of human diseases scan for more than one locus at a time. To overcome some of the statistical and computational limitations of a simultaneous search for two disease susceptibility loci in the presence of epistasis, we developed new score statistics to simultaneously scan for two disease susceptibility loci in pedigree data. These model-free score statistics are based on developments for model-free maximum lod scores, which in turn are based on variance components for indicators of disease status. To overcome reduced power caused by many parameters in the general two-locus model, we impose constraints on ratios of variance components, much like those used for robust single-locus linkage statistics (e.g., minimax constraints). The resulting three-degree of freedom score statistic, constrained as a one-sided multivariate test, can be computed rapidly, making simultaneous search feasible for human genetic linkage studies. Furthermore, using recent developments to rapidly compute simulation P-values for score statistics, it is feasible to empirically evaluate the statistical significance of the proposed score statistics. Application of these methods to two large studies of the genetic linkage of prostate cancer illuminates their strengths and limitations. The results provide weak suggestions for linkage of several pairs of chromosomal regions (chromosome pairs 1-21, 3-13, 5-9, and 14-19), all of which showed stronger linkage signals when the score statistics accounted for epistasis. These novel score statistics should prove useful for linkage studies of other complex human diseases.
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Affiliation(s)
- Daniel J Schaid
- Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA.
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Pierce BL, Friedrichsen-Karyadi DM, McIntosh L, Deutsch K, Hood L, Ostrander EA, Austin MA, Stanford JL. Genomic scan of 12 hereditary prostate cancer families having an occurrence of pancreas cancer. Prostate 2007; 67:410-5. [PMID: 17192958 DOI: 10.1002/pros.20527] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Prostate cancer is a genetically heterogeneous disease. Using the occurrence of other cancers in hereditary prostate cancer (HPC) families is a promising strategy for developing genetically homogeneous data sets that can enhance the ability to identify susceptibility loci using linkage analysis. METHODS Twelve HPC families with the co-occurrence of adenocarcinoma of the pancreas were selected from the Prostate Cancer Genetic Research Study (PROGRESS). Non-parametric linkage analysis for a prostate/pancreas cancer susceptibility phenotype was performed using 441 genome-wide microsatellite markers. RESULTS No statistically significant linkage signal was detected in this analysis. The strongest linkage signals, as measured by Kong and Cox LOD score (KC LOD), were observed on chromosomes 2q37.2-q37.3 (KC LOD = 1.01; P = 0.02) and 16q23.2 (KC LOC = 1.05; P = 0.01). CONCLUSIONS Despite the lack of statistically significant findings, four chromosomal regions, three of which (2q, 16q, 17q) were previously noted as harboring potential susceptibility loci, showed suggestive linkage results in this scan.
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Affiliation(s)
- Brandon L Pierce
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA
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Camp NJ, Farnham JM, Cannon-Albright LA. Localization of a Prostate Cancer Predisposition Gene to an 880-kb Region on Chromosome 22q12.3 in Utah High-Risk Pedigrees. Cancer Res 2006; 66:10205-12. [PMID: 17047086 DOI: 10.1158/0008-5472.can-06-1233] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Chromosome 22q has become recently a region of interest for prostate cancer. We identified previously a logarithm of odds (LOD) of 2.42 at chromosome 22q12.3. Additionally, this region has been noted by eight other studies, with linkage evidence ranging from LOD of 1.50 to 3.57. Here, we do fine mapping and localization of the region using a pedigree-specific recombinant mapping approach in 14 informative, high-risk Utah pedigrees. These 14 pedigrees were chosen because they were either "linked" or "haplotype-sharing" pedigrees or both. "Linked" pedigrees were those with significant pedigree-specific linkage evidence (LOD, >0.588; P < 0.05) to the 22q12.3 region, regardless of the number of prostate cancer cases sharing the segregating haplotype. "Haplotype-sharing" pedigrees were those with at least five prostate cancer cases sharing a segregating haplotype in the 22q12.3 region, regardless of the linkage evidence. In each pedigree, the most likely haplotype configuration (in addition to the multipoint LOD graph for linked pedigrees) was used to infer the position of recombinant events and delimit the segregating chromosomal segment in each pedigree. These pedigree-specific chromosomal segments were then overlaid to form a consensus recombinant map across all 14 pedigrees. Using this method, we identified a 881,538-bp interval at 22q12.3, between D22S1265 and D22S277, which is the most likely region that contains the 22q prostate cancer predisposition gene. The unique Utah extended high-risk pedigree resource allows this powerful localization approach in pedigrees with evidence for segregating predisposition to prostate cancer. We are mutation screening candidate genes in this region to identify specific genetic variants segregating in these pedigrees.
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Affiliation(s)
- Nicola J Camp
- Division of Genetic Epidemiology, Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, Utah 84108, USA.
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Schaid DJ, McDonnell SK, Zarfas KE, Cunningham JM, Hebbring S, Thibodeau SN, Eeles RA, Easton DF, Foulkes WD, Simard J, Giles GG, Hopper JL, Mahle L, Moller P, Badzioch M, Bishop DT, Evans C, Edwards S, Meitz J, Bullock S, Hope Q, Guy M, Hsieh CL, Halpern J, Balise RR, Oakley-Girvan I, Whittemore AS, Xu J, Dimitrov L, Chang BL, Adams TS, Turner AR, Meyers DA, Friedrichsen DM, Deutsch K, Kolb S, Janer M, Hood L, Ostrander EA, Stanford JL, Ewing CM, Gielzak M, Isaacs SD, Walsh PC, Wiley KE, Isaacs WB, Lange EM, Ho LA, Beebe-Dimmer JL, Wood DP, Cooney KA, Seminara D, Ikonen T, Baffoe-Bonnie A, Fredriksson H, Matikainen MP, Tammela TLJ, Bailey-Wilson J, Schleutker J, Maier C, Herkommer K, Hoegel JJ, Vogel W, Paiss T, Wiklund F, Emanuelsson M, Stenman E, Jonsson BA, Grönberg H, Camp NJ, Farnham J, Cannon-Albright LA, Catalona WJ, Suarez BK, Roehl KA. Pooled genome linkage scan of aggressive prostate cancer: results from the International Consortium for Prostate Cancer Genetics. Hum Genet 2006; 120:471-85. [PMID: 16932970 DOI: 10.1007/s00439-006-0219-9] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2006] [Accepted: 06/05/2006] [Indexed: 10/24/2022]
Abstract
While it is widely appreciated that prostate cancers vary substantially in their propensity to progress to a life-threatening stage, the molecular events responsible for this progression have not been identified. Understanding these molecular mechanisms could provide important prognostic information relevant to more effective clinical management of this heterogeneous cancer. Hence, through genetic linkage analyses, we examined the hypothesis that the tendency to develop aggressive prostate cancer may have an important genetic component. Starting with 1,233 familial prostate cancer families with genome scan data available from the International Consortium for Prostate Cancer Genetics, we selected those that had at least three members with the phenotype of clinically aggressive prostate cancer, as defined by either high tumor grade and/or stage, resulting in 166 pedigrees (13%). Genome-wide linkage data were then pooled to perform a combined linkage analysis for these families. Linkage signals reaching a suggestive level of significance were found on chromosomes 6p22.3 (LOD = 3.0), 11q14.1-14.3 (LOD = 2.4), and 20p11.21-q11.21 (LOD = 2.5). For chromosome 11, stronger evidence of linkage (LOD = 3.3) was observed among pedigrees with an average at diagnosis of 65 years or younger. Other chromosomes that showed evidence for heterogeneity in linkage across strata were chromosome 7, with the strongest linkage signal among pedigrees without male-to-male disease transmission (7q21.11, LOD = 4.1), and chromosome 21, with the strongest linkage signal among pedigrees that had African American ancestry (21q22.13-22.3; LOD = 3.2). Our findings suggest several regions that may contain genes which, when mutated, predispose men to develop a more aggressive prostate cancer phenotype. This provides a basis for attempts to identify these genes, with potential clinical utility for men with aggressive prostate cancer and their relatives.
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Affiliation(s)
- Daniel J Schaid
- Harwick 7, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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Datta MW, Hernandez AM, Schlicht MJ, Kahler AJ, DeGueme AM, Dhir R, Shah RB, Farach-Carson C, Barrett A, Datta S. Perlecan, a candidate gene for the CAPB locus, regulates prostate cancer cell growth via the Sonic Hedgehog pathway. Mol Cancer 2006; 5:9. [PMID: 16507112 PMCID: PMC1421430 DOI: 10.1186/1476-4598-5-9] [Citation(s) in RCA: 73] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2005] [Accepted: 03/01/2006] [Indexed: 12/24/2022] Open
Abstract
Background Genetic studies associated the CAPB locus with familial risk of brain and prostate cancers. We have identified HSPG2 (Perlecan) as a candidate gene for CAPB. Previously we have linked Perlecan to Hedgehog signaling in Drosophila. More recently, we have demonstrated the importance of Hedgehog signaling in humans for advanced prostate cancer. Results Here we demonstrate Perlecan expression in prostate cancer, and its function in prostate cancer cell growth through interaction and modulation of Sonic Hedgehog (SHH) signaling. Perlecan expression in prostate cancer tissues correlates with a high Gleason score and rapid cell proliferation. Perlecan is highly expressed in prostate cancer cell lines, including androgen insensitive cell lines and cell lines selected for metastatic properties. Inhibition of Perlecan expression in these cell lines decreases cell growth. Simultaneous blockade of Perlecan expression and androgen signaling in the androgen-sensitive cell line LNCaP was additive, indicating the independence of these two pathways. Perlecan expression correlates with SHH in tumor tissue microarrays and increased tumor cell proliferation based on Ki-67 immunohistochemistry. Inhibition of Perlecan expression by siRNA in prostate cancer cell lines decreases SHH signaling while expression of the downstream SHH effector GLI1 rescues the proliferation defect. Perlecan forms complexes with increasing amounts of SHH that correlate with increasing metastatic potential of the prostate cancer cell line. SHH signaling also increases in the more metastatic cell lines. Metastatic prostate cancer cell lines grown under serum-starved conditions (low androgen and growth factors) resulted in maintenance of Perlecan expression. Under low androgen, low growth factor conditions, Perlecan expression level correlates with the ability of the cells to maintain SHH signaling. Conclusion We have demonstrated that Perlecan, a candidate gene for the CAPB locus, is a new component of the SHH pathway in prostate tumors and works independently of androgen signaling. In metastatic tumor cells increased SHH signaling correlates with the maintenance of Perlecan expression and more Perlecan-SHH complexes. Perlecan is a proteoglycan that regulates extracellular and stromal accessibility to growth factors such as SHH, thus allowing for the maintenance of SHH signaling under growth factor limiting conditions. This proteoglycan represents an important central regulator of SHH activity and presents an ideal drug target for blocking SHH effects.
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Affiliation(s)
- Milton W Datta
- Departments of Pathology and Urology, Emory University, Atlanta, GA, 30322, USA
| | - Ana Maria Hernandez
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, Texas 77843-2128, USA
| | - Michael J Schlicht
- Departments of Pathology and Urology, Emory University, Atlanta, GA, 30322, USA
| | - Andrea J Kahler
- Departments of Pathology and Urology, Emory University, Atlanta, GA, 30322, USA
| | - Amy M DeGueme
- Departments of Pathology and Urology, Emory University, Atlanta, GA, 30322, USA
| | - Rajiv Dhir
- Department of Pathology, University of Pittsburgh Medical Center, 200 Lothrop Street, Pittsburgh PA, 15232, USA
| | - Rajal B Shah
- Department of Pathology, University of Michigan, 1500 Catherine Ave, Ann Arbor, MI, 48109, USA
| | - Cindy Farach-Carson
- Department of Biological Sciences, University of Delaware, 304 Wolfe Hall, Newark, DE, 19716, USA
| | - Andrea Barrett
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, Texas 77843-2128, USA
| | - Sumana Datta
- Department of Biochemistry and Biophysics, Texas A&M University, 2128 TAMU, College Station, Texas 77843-2128, USA
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Stanford JL, McDonnell SK, Friedrichsen DM, Carlson EE, Kolb S, Deutsch K, Janer M, Hood L, Ostrander EA, Schaid DJ. Prostate cancer and genetic susceptibility: a genome scan incorporating disease aggressiveness. Prostate 2006; 66:317-25. [PMID: 16245279 DOI: 10.1002/pros.20349] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Prostate cancer is a heterogeneous disease, both genetically and phenotypically. Linkage studies attempting to map genes for hereditary prostate cancer (HPC) have proved challenging, and one potential problem contributing to this challenge is the variability in disease phenotypes. METHODS We collected clinical data on 784 affected men with prostate cancer from 248 HPC families for whom a genomic screen was performed. Disease characteristics (i.e., Gleason score, stage, prostate-specific antigen (PSA)) were used to classify affected men into categories of clinically insignificant, moderate, or aggressive prostate cancer. To potentially enrich for a genetic etiology, we restricted linkage analyses to only men with aggressive disease, although we used genotype information from all family members; linkage analyses used both dominant and recessive models. In addition, subset analyses considered age at diagnosis, number of affected men per family and other stratifications to try to increase genetic homogeneity. RESULTS Several regions of interest (heterogeneity LOD score, HLOD>1.0) were identified in families (n=123) with >or=2 affecteds with aggressive prostate cancer. "Suggestive" linkage was observed at chromosome 22q11.1 (Dominant model HLOD=2.18) and the result was stronger (Dominant HLOD=2.75) in families with evidence of male-to-male transmission. A second region at 22q12.3-q13.1 was also highlighted (Recessive model HLOD=1.90) among men with aggressive disease, as was a region on chromosome 18. CONCLUSIONS These analyses suggest that using clinically defined phenotypes may be a useful approach for simplifying the locus heterogeneity problems that confound the search for prostate cancer susceptibility genes.
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Affiliation(s)
- Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, and Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, Washington 98109-1024, USA.
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Zheng SL, Ju JH, Chang BL, Ortner E, Sun J, Isaacs SD, Sun J, Wiley KE, Liu W, Zemedkun M, Walsh PC, Ferretti J, Gruschus J, Isaacs WB, Gelmann EP, Xu J. Germ-Line Mutation of NKX3.1 Cosegregates with Hereditary Prostate Cancer and Alters the Homeodomain Structure and Function. Cancer Res 2006; 66:69-77. [PMID: 16397218 DOI: 10.1158/0008-5472.can-05-1550] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
NKX3.1, a gene mapped to 8p21, is a member of the NK class of homeodomain proteins and is expressed primarily in the prostate. NKX3.1 exerts a growth-suppressive and differentiating effect on prostate epithelial cells. Because of its known functions and its location within a chromosomal region where evidence for prostate cancer linkage and somatic loss of heterozygosity is found, we hypothesize that sequence variants in the NKX3.1 gene increase prostate cancer risk. To address this, we first resequenced the NKX3.1 gene in 159 probands of hereditary prostate cancer families recruited at Johns Hopkins Hospital; each family has at least three first-degree relatives affected with prostate cancer. Twenty-one germ-line variants were identified in this analysis, including one previously described common nonsynonymous change (R52C), two novel rare nonsynonymous changes (A17T and T164A), and a novel common 18-bp deletion in the promoter. Overall, the germ-line variants were significantly linked to prostate cancer, with a peak heterogeneity logarithm of odds of 2.04 (P = 0.002) at the NKX3.1 gene. The rare nonsynonymous change, T164A, located in the homeobox domain of the gene, segregated with prostate cancer in a family with three affected brothers and one unaffected brother. Importantly, nuclear magnetic resonance solution structure analysis and circular dichroism studies showed this specific mutation to affect the stability of the homeodomain of the NKX3.1 protein and decreased binding to its cognate DNA recognition sequence. These results suggest that germ-line sequence variants in NKX3.1 may play a role in susceptibility to hereditary prostate cancer and underscore a role for NKX3.1 as a prostate cancer gatekeeper.
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Affiliation(s)
- S Lilly Zheng
- Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
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Abstract
Linkage analysis provides an important tool for mapping genes for complex disease. However its usefulness has been limited by inadequate marker density, inadequate sample sizes and the possibility that different genes account for different subtypes of the disease (phenotypic heterogeneity). The first two limitations can be addressed by high-density single nucleotide polymorphism (SNP) genotyping and the pooling of large sets of multiple-case families. Phenotypic heterogeneity can be addressed by analyses that weigh the contributions of affected family members according to characteristics of their disease phenotypes. Here we introduce a method for including such person-specific weights in nonparametric linkage analysis. We show with simulations that such weighting can provide stronger linkage signals when a causal polymorphism affects some manifestations of the disease more than others. We applied the method to prostate cancer linkage data in a region on chromosome 19p, and obtained higher lod scores by assigning weights of one to men with early-onset aggressive cancers, weights of zero to those with late-onset nonaggressive cancers, and intermediate weights to all other affected men. We have developed a modified version of GENEHUNTER that allows inclusion of person-specific weights in the nonparametric analyses. This program is freely available at http://med.stanford.edu/epidemiology/statisticalSoftware/weightedKAC.
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Affiliation(s)
- Alice S Whittemore
- Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California 94305-5405, USA.
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40
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Camp NJ, Farnham JM, Cannon Albright LA. Genomic search for prostate cancer predisposition loci in Utah pedigrees. Prostate 2005; 65:365-74. [PMID: 16037989 DOI: 10.1002/pros.20287] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND We report a genome linkage scan in extended Utah pedigrees, utilizing a pedigree-splitting approach to reduce intra-familial heterogeneity. METHODS Fifty-nine pedigrees with at least four Prostate cancer (PrCa) cases and no more than two meioses separating PrCa cases were analyzed using the CIDR genomic search STRP marker set. Parametric linkage analyses using dominant and recessive models were performed on four datasets resulting from a pedigree splitting algorithm. In addition, age at diagnosis subset analyses were performed. RESULTS Four regions of interest (LODs>1.9) were identified on chromosomes 1p, 3q, 5q, and 22q. The linkage peaks on 1p, 3q, and 22q have been previously implicated for PrCa, though not significantly. The 1p region was supported by a single large Utah pedigree with a multipoint LOD score of 3.1. An additional 10 regions gave LOD scores>1.22 (nominal linkage evidence), including moderate evidence supporting the HPC20 region with a recessive model. CONCLUSIONS Our genome-wide search in the informative, extended Utah pedigrees continues to illustrate an ability to identify and replicate linkage peaks, and supports four regions of interest for PrCa predisposition genes.
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Affiliation(s)
- Nicola J Camp
- Genetic Epidemiology, Department of Medical Informatics, University of Utah, Salt Lake City, Utah 84108, USA
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41
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Chang BL, Lange EM, Dimitrov L, Valis CJ, Gillanders EM, Lange LA, Wiley KE, Isaacs SD, Wiklund F, Baffoe-Bonnie A, Langefeld CD, Zheng SL, Matikainen MP, Ikonen T, Fredriksson H, Tammela T, Walsh PC, Bailey-Wilson JE, Schleutker J, Gronberg H, Cooney KA, Isaacs WB, Suh E, Trent JM, Xu J. Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect. Hum Genet 2005; 118:716-24. [PMID: 16328469 DOI: 10.1007/s00439-005-0099-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2005] [Accepted: 09/26/2005] [Indexed: 10/25/2022]
Abstract
Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene-gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene-gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Umeå, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P< or =0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene-gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.
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Affiliation(s)
- Bao-Li Chang
- Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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42
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Xu J, Dimitrov L, Chang BL, Adams TS, Turner AR, Meyers DA, Eeles RA, Easton DF, Foulkes WD, Simard J, Giles GG, Hopper JL, Mahle L, Moller P, Bishop T, Evans C, Edwards S, Meitz J, Bullock S, Hope Q, Hsieh CL, Halpern J, Balise RN, Oakley-Girvan I, Whittemore AS, Ewing CM, Gielzak M, Isaacs SD, Walsh PC, Wiley KE, Isaacs WB, Thibodeau SN, McDonnell SK, Cunningham JM, Zarfas KE, Hebbring S, Schaid DJ, Friedrichsen DM, Deutsch K, Kolb S, Badzioch M, Jarvik GP, Janer M, Hood L, Ostrander EA, Stanford JL, Lange EM, Beebe-Dimmer JL, Mohai CE, Cooney KA, Ikonen T, Baffoe-Bonnie A, Fredriksson H, Matikainen MP, Tammela TLJ, Bailey-Wilson J, Schleutker J, Maier C, Herkommer K, Hoegel JJ, Vogel W, Paiss T, Wiklund F, Emanuelsson M, Stenman E, Jonsson BA, Grönberg H, Camp NJ, Farnham J, Cannon-Albright LA, Seminara D. A combined genomewide linkage scan of 1,233 families for prostate cancer-susceptibility genes conducted by the international consortium for prostate cancer genetics. Am J Hum Genet 2005; 77:219-29. [PMID: 15988677 PMCID: PMC1224525 DOI: 10.1086/432377] [Citation(s) in RCA: 113] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2005] [Accepted: 05/27/2005] [Indexed: 11/03/2022] Open
Abstract
Evidence of the existence of major prostate cancer (PC)-susceptibility genes has been provided by multiple segregation analyses. Although genomewide screens have been performed in over a dozen independent studies, few chromosomal regions have been consistently identified as regions of interest. One of the major difficulties is genetic heterogeneity, possibly due to multiple, incompletely penetrant PC-susceptibility genes. In this study, we explored two approaches to overcome this difficulty, in an analysis of a large number of families with PC in the International Consortium for Prostate Cancer Genetics (ICPCG). One approach was to combine linkage data from a total of 1,233 families to increase the statistical power for detecting linkage. Using parametric (dominant and recessive) and nonparametric analyses, we identified five regions with "suggestive" linkage (LOD score >1.86): 5q12, 8p21, 15q11, 17q21, and 22q12. The second approach was to focus on subsets of families that are more likely to segregate highly penetrant mutations, including families with large numbers of affected individuals or early age at diagnosis. Stronger evidence of linkage in several regions was identified, including a "significant" linkage at 22q12, with a LOD score of 3.57, and five suggestive linkages (1q25, 8q13, 13q14, 16p13, and 17q21) in 269 families with at least five affected members. In addition, four additional suggestive linkages (3p24, 5q35, 11q22, and Xq12) were found in 606 families with mean age at diagnosis of < or = 65 years. Although it is difficult to determine the true statistical significance of these findings, a conservative interpretation of these results would be that if major PC-susceptibility genes do exist, they are most likely located in the regions generating suggestive or significant linkage signals in this large study.
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Affiliation(s)
- Jianfeng Xu
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Latchezar Dimitrov
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Bao-Li Chang
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Tamara S. Adams
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Aubrey R. Turner
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Deborah A. Meyers
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Rosalind A. Eeles
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Douglas F. Easton
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - William D. Foulkes
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Jacques Simard
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Graham G. Giles
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - John L. Hopper
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Lovise Mahle
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Pal Moller
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Tim Bishop
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Chris Evans
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Steve Edwards
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Julia Meitz
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Sarah Bullock
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Questa Hope
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - ACTANE Consortium
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Chih-lin Hsieh
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Jerry Halpern
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Raymond N. Balise
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Ingrid Oakley-Girvan
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Alice S. Whittemore
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Charles M. Ewing
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Marta Gielzak
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Sarah D. Isaacs
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Patrick C. Walsh
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kathleen E. Wiley
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - William B. Isaacs
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Stephen N. Thibodeau
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Shannon K. McDonnell
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Julie M. Cunningham
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Katherine E. Zarfas
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Scott Hebbring
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Daniel J. Schaid
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Danielle M. Friedrichsen
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kerry Deutsch
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Suzanne Kolb
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Michael Badzioch
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Gail P. Jarvik
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Marta Janer
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Leroy Hood
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Elaine A. Ostrander
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Janet L. Stanford
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Ethan M. Lange
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Jennifer L. Beebe-Dimmer
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Caroline E. Mohai
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kathleen A. Cooney
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Tarja Ikonen
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Agnes Baffoe-Bonnie
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Henna Fredriksson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Mika P. Matikainen
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Teuvo LJ Tammela
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Joan Bailey-Wilson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Johanna Schleutker
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Christiane Maier
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kathleen Herkommer
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Josef J. Hoegel
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Walther Vogel
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Thomas Paiss
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Fredrik Wiklund
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Monica Emanuelsson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Elisabeth Stenman
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Björn-Anders Jonsson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Henrik Grönberg
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Nicola J. Camp
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - James Farnham
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Lisa A. Cannon-Albright
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Daniela Seminara
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
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43
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Schaid DJ, Chang BL. Description of the International Consortium For Prostate Cancer Genetics, and failure to replicate linkage of hereditary prostate cancer to 20q13. Prostate 2005; 63:276-90. [PMID: 15599943 DOI: 10.1002/pros.20198] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The International Consortium for Prostate Cancer Genetics (ICPCG) is an international collaborative effort to pool pedigrees with hereditary prostate cancer (PC) in order to replicate linkage findings for PC. A strength of the ICPCG is the large number of well-characterized pedigrees, allowing linkage analyses within large subsets. Given the heterogeneity and complexity of PC, the historical difficulties of synthesizing different studies reporting positive and negative linkage replication, and the use of different statistical analysis methods and different stratification criteria, the ICPCG provides a valuable resource to evaluate linkage for hereditary PC. To date, linkage of chromosome 20 (HPC20) to hereditary PC has been one of the strongest linkage signals, yet the efforts to replicate this linkage have been limited. This paper reports a linkage analysis of chromosome 20 markers for 1,234 pedigrees with multiple cases of PC ascertained through the ICPCG, and represents the most thorough attempt to confirm or refute linkage to chromosome 20. From the original 158 Mayo pedigrees in which linkage was detected, the maximum heterogeneity LOD (HLOD) score, under a recessive model, was 2.78. In contrast, for the 1,076 pedigrees not included in the original study, the maximum HLOD score (recessive model) was 0.06. Although, a few small linkage signals for chromosome 20 were found in various strata of this pooled analysis, this large study failed to replicate linkage to HPC20. This study illustrates the value of the ICPCG family collection to evaluate reported linkage signals and suggests that the HPC20 region does not make a major contribution to PC susceptibility.
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Affiliation(s)
- Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
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44
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Schaid DJ, Guenther JC, Christensen GB, Hebbring S, Rosenow C, Hilker CA, McDonnell SK, Cunningham JM, Slager SL, Blute ML, Thibodeau SN. Comparison of microsatellites versus single-nucleotide polymorphisms in a genome linkage screen for prostate cancer-susceptibility Loci. Am J Hum Genet 2004; 75:948-65. [PMID: 15514889 PMCID: PMC1182157 DOI: 10.1086/425870] [Citation(s) in RCA: 117] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2004] [Accepted: 09/08/2004] [Indexed: 12/19/2022] Open
Abstract
Prostate cancer is one of the most common cancers among men and has long been recognized to occur in familial clusters. Brothers and sons of affected men have a 2-3-fold increased risk of developing prostate cancer. However, identification of genetic susceptibility loci for prostate cancer has been extremely difficult. Although the suggestion of linkage has been reported for many chromosomes, the most promising regions have been difficult to replicate. In this study, we compare genome linkage scans using microsatellites with those using single-nucleotide polymorphisms (SNPs), performed in 467 men with prostate cancer from 167 families. For the microsatellites, the ABI Prism Linkage Mapping Set version 2, with 402 microsatellite markers, was used, and, for the SNPs, the Early Access Affymetrix Mapping 10K array was used. Our results show that the presence of linkage disequilibrium (LD) among SNPs can lead to inflated LOD scores, and this seems to be an artifact due to the assumption of linkage equilibrium that is required by the current genetic-linkage software. After excluding SNPs with high LD, we found a number of new LOD-score peaks with values of at least 2.0 that were not found by the microsatellite markers: chromosome 8, with a maximum model-free LOD score of 2.2; chromosome 2, with a LOD score of 2.1; chromosome 6, with a LOD score of 4.2; and chromosome 12, with a LOD score of 3.9. The LOD scores for chromosomes 6 and 12 are difficult to interpret, because they occurred only at the extreme ends of the chromosomes. The greatest gain provided by the SNP markers was a large increase in the linkage information content, with an average information content of 61% for the SNPs, versus an average of 41% for the microsatellite markers. The strengths and weaknesses of microsatellite versus SNP markers are illustrated by the results of our genome linkage scans.
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Affiliation(s)
- Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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Abstract
Prostate cancer is a heterogeneous disease with multiple loci contributing to susceptibility. Traditionally, genome-wide scans using high-risk families have utilized stratification by number of affected individuals, family history of other cancers, or family age at diagnosis to improve genetic homogeneity. In addition to locus heterogeneity, for later onset diseases such as prostate cancer, a major limitation to mapping efforts is that key parental DNA samples are rarely available. The lack of available samples from upper generations reduces inheritance information, and as a result, the standard 10-cM genome scan does not provide full power to detect linkage. To increase the ability to find disease-associated loci, much denser genome-wide scans must be undertaken in multiple ethnic groups. In addition, new ways of defining homogenous subsets of families need to be developed.
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Affiliation(s)
- Elaine A Ostrander
- Division of Clinical Research1, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA.
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Edwards SM, Eeles RA. Unravelling the genetics of prostate cancer. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2004; 129C:65-73. [PMID: 15264274 DOI: 10.1002/ajmg.c.30027] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
This review describes what is currently known about the genetics of prostate cancer. Traditionally, the genetics of a suspected inherited cancer predisposition have generally been thought of in terms of a single, high-risk gene with a dominant mode of inheritance. Such a gene might be observed in families, as has been documented in familial breast cancer (BRCA1/2), familial colorectal cancer (HNPCC), retinoblastoma (RB1), and Wilms tumor (WT1). This review investigates the evidence for the existence, first of familial prostate cancer, and second, for the presence of such a high-risk gene in those families by epidemiological and experimental approaches. Another current area of interest in prostate cancer is the investigation of the contribution of common lower penetrance genes to the disease. This alternative approach has become popular, as it raises the issue of frequently seen genetic variations such as single nucleotide polymorphisms (SNPs) having relevance to the risk of developing the disease. Finally, this article will explore the way forward, with emphasis on worldwide collaboration from teams attempting to find the genes responsible for the disease and investment in new technologies that will aid in their discovery.
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Affiliation(s)
- Stephen M Edwards
- Translational Cancer Genetics Team, Institute of Cancer Research, Sutton, Surrey SM2 5NG, UK
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Kommu S, Edwards S, Eeles R. The clinical genetics of prostate cancer. Hered Cancer Clin Pract 2004; 2:111-21. [PMID: 20233465 PMCID: PMC4392519 DOI: 10.1186/1897-4287-2-3-111] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2004] [Accepted: 07/27/2004] [Indexed: 12/24/2022] Open
Abstract
Prostate cancer is the most common cancer in men and the second highest cause of cancer-related mortality in the U.K. A genetic component in predisposition to prostate cancer has been recognized for decades. One of the strongest epidemiological risk factors for prostate cancer is a positive family history. The hunt for the genes that predispose to prostate cancer in families has been the focus of many research groups worldwide for the past 10 years. Both epidemiological and twin studies support a role for genetic predisposition to prostate cancer. Familial cancer loci have been found, but the genes that cause familial prostate cancer remain largely elusive. Unravelling the genetics of prostate cancer is challenging and is likely to involve the analysis of numerous predisposition genes. Current evidence supports the hypothesis that excess familial risk of prostate cancer could be due to the inheritance of multiple moderate-risk genetic variants. Although research on hereditary prostate cancer has improved our knowledge of the genetic aetiology of the disease, a lot of questions still remain unanswered. This article explores the current evidence that there is a genetic component to the aetiology of prostate cancer and attempts to put into context the diverse findings that have been shown to be possibly associated with the development of hereditary prostate cancer. Linkage searches over the last decade are summarised. It explores issues as to why understanding the genetics of prostate cancer has been so difficult and why despite this, it is still a major focus of research. Finally, current and future management strategies of men with Hereditary Prostate Cancer (HPC) are discussed.
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Affiliation(s)
- Sashi Kommu
- Reader in Clinical Cancer Genetics, Translational Cancer Genetics Team, Institute of Cancer Research, Sutton, UK.
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Friedrichsen DM, Stanford JL, Isaacs SD, Janer M, Chang BL, Deutsch K, Gillanders E, Kolb S, Wiley KE, Badzioch MD, Zheng SL, Walsh PC, Jarvik GP, Hood L, Trent JM, Isaacs WB, Ostrander EA, Xu J. Identification of a prostate cancer susceptibility locus on chromosome 7q11-21 in Jewish families. Proc Natl Acad Sci U S A 2004; 101:1939-44. [PMID: 14769943 PMCID: PMC357031 DOI: 10.1073/pnas.0308336100] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Results from over a dozen prostate cancer susceptibility genome-wide scans, encompassing some 1,500 hereditary prostate cancer families, indicate that prostate cancer is an extremely heterogeneous disease with multiple loci contributing to overall susceptibility. In an attempt to reduce locus heterogeneity, we performed a genomewide linkage scan for prostate cancer susceptibility genes with 36 Jewish families, which represent a stratification of hereditary prostate cancer families with potentially increased locus homogeneity. The 36 Jewish families represent a combined dataset of 17 Jewish families from the Fred Hutchinson Cancer Research Center-based Prostate Cancer Genetic Research Study dataset and 19 Ashkenazi Jewish families collected at Johns Hopkins University. All available family members, including 94 affected men, were genotyped at markers distributed across the genome with an average interval of <10 centimorgans. Nonparametric multipoint linkage analyses were the primary approach, although parametric analyses were performed as well. Our strongest signal was a significant linkage peak at 7q11-21, with a nonparametric linkage (NPL) score of 3.01 (P = 0.0013). Simulations indicated that this corresponds to a genomewide empirical P = 0.006. All other regions had NPL P values >/=0.02. After genotyping additional markers within the 7q11-21 peak, the NPL score increased to 3.35 (P = 0.0004) at D7S634 with an allele-sharing logarithm of odds of 3.12 (P = 0.00007). These studies highlight the utility of analyzing defined sets of families with a common origin for reducing locus heterogeneity problems associated with studying complex traits.
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Affiliation(s)
- Danielle M Friedrichsen
- Divisions of Clinical Research and Human Biology and Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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Easton DF, Schaid DJ, Whittemore AS, Isaacs WJ. Where are the prostate cancer genes?--A summary of eight genome wide searches. Prostate 2003; 57:261-9. [PMID: 14601022 DOI: 10.1002/pros.10300] [Citation(s) in RCA: 93] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND There is strong evidence for genetic susceptibility to prostate cancer, but most of the genes underlying this susceptibility remain to be identified. METHODS We reviewed the results of eight genome-wide linkage searches based on 1,293 families with multiple cases of prostate cancer. RESULTS Across these studies, 11 linkage peaks with LOD scores in excess of 2 were identified. However, no chromosomal region was reported as significant at this level by more than one study and only one corresponded to a peak previously suggested by another group. CONCLUSIONS These results indicate that prostate cancer is genetically complex, and that combined analyses of large family sets will be required to evaluate reliably the linkage evidence.
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Affiliation(s)
- Douglas F Easton
- Cancer Research U.K. Genetic Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, United Kingdom.
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